Search for a path or avoidance of an obstacle is the most essential technique in autonomous travel of a mobile robot. A mobile robot travels along the path generated up to the destination point and must arrive at the destination point without colliding any peripheral obstacle. Hereinafter, a good path means the shortest path that minimizes the traveling path to the destination point or a safe path that minimizes the probability of collision with peripheral obstacles. In general, a safe path is of greater importance than a good path in robot applications; however, the most ideal path would be one that is the safest as well as the shortest as possible.
In order to ensure a safe path, in general, it has been customary to determine the travel direction of a robot by taking into consideration both the direction in which free space is most available and the direction toward the destination point, the former being searched by using obstacle detection sensors equipped on a robot (such as laser and ultrasound devices that can measure a distance to peripheral obstacles). Weights of the direction towards the free space and of the direction towards the destination point are determined by experiments. While it is possible to decrease the possibility of collision with obstacles by increasing the weight on the free space, this would give rise to a situation in which the robot should take a long detour or, in an extreme case, cannot arrive at the destination point. On the other hand, an increased weight on the destination point would result in less safety in the path. As such, the travel performance of a robot is greatly influenced by the weights.
Because the optimal weights depend on the spatial configurations of the obstacles or circumstances in which the robot is operated, one has to adjust the weights experimentally in order to cope with these factors. A well-known extreme example is given by a situation the destination point is located on the other side of a U-shaped obstacle; quite often than not, the robot is not able to go through to the destination point, once it gets in the obstacle.
The safety of a travel path of a robot hinges primarily on the amount of the safe distance from peripheral obstacles that exist along the travel path. In existing methods, the safety of a travel path is estimated by weights between the safest direction (in which the free space is permitted the most) and the destination point direction and, therefore, it is extremely difficult to determine intuitively the safe distance to the obstacle under consideration. For example, if the two weights are identical and the destination point direction lies exactly opposite to the safest direction, then the robot would move sideways in a direction perpendicular to both of them. When the destination point lies at the end of a passage that narrows down, the safest direction would lie in the direction away from the destination point, and hence the robot could, as normally desired, arrive at the destination point, should a greater weight be given to the destination point direction. Because effects of the weights on determination of the travel path are not intuitive, under general circumstances a great number of experiments should be carried out to find the optimal weights. It should be also noted that the optimal weights may not be found at all in some extreme cases.